It is argued that infants build a foundation for learning about the world through their incidental acquisition of the spatial and temporal regularities surrounding them. A challenge is that learning occurs across multiple contexts whose statistics can greatly differ. Two artificial language studies with 12-month-olds demonstrate that infants come prepared to parse statistics across contexts using the temporal and perceptual features that distinguish one context from another. These results suggest that infants can organize their statistical input with a wider range of features that typically considered. Possible attention, decision making, and memory mechanisms are discussed.

It is argued that infants build a foundation for learning about the world through their incidental acquisition of the spatial and temporal regularities surrounding them. A challenge is that learning occurs across multiple contexts whose statistics can greatly differ. Two artificial language studies with 12-month-olds demonstrate that infants come prepared to parse statistics across contexts using the temporal and perceptual features that distinguish one context from another. These results suggest that infants can organize their statistical input with a wider range of features that typically considered. Possible attention, decision making, and memory mechanisms are discussed.

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dc.type

text

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dc.type

Electronic Dissertation

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dc.subject

dynamic change

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dc.subject

exemplar theory

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dc.subject

statistical learning

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dc.subject

Psychology

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dc.subject

artificial language learning

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thesis.degree.name

Ph.D.

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thesis.degree.level

doctoral

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thesis.degree.discipline

Graduate College

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thesis.degree.discipline

Psychology

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thesis.degree.grantor

University of Arizona

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dc.contributor.advisor

Gómez, Rebecca L.

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dc.contributor.committeemember

Gómez, Rebecca L.

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dc.contributor.committeemember

Gerken, LouAnn

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dc.contributor.committeemember

Lotto, Andrew J.

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